code: def testWeightsNonzero(self):
      inputs = tf.constant([[3, 1, 0], [1, 0, 0]])
  
      graph = mtf.Graph()
      mesh = mtf.Mesh(graph, "my_mesh")
      batch_dim = mtf.Dimension("batch", inputs.shape.as_list()[0])
      channels_dim = mtf.Dimension(
          "channels", inputs.shape.as_list()[1]
      )
  
      mtf_inputs = mtf.import_tf_tensor(
          mesh, inputs, shape=mtf.Shape([batch_dim, channels_dim])
      )
      mtf_outputs = mtf.layers.weights_nonzero(mtf_inputs)
      mesh_impl = mtf.placement_mesh_impl.PlacementMeshImpl(
          shape=[], layout={}, devices=[""]
      )
      lowering = mtf.Lowering(graph, {mesh: mesh_impl})
      actual_outputs = lowering.export_to_tf_tensor(mtf_outputs)
  
      expected_outputs = tf.cast(tf.not_equal(inputs, 0), tf.float32)
      tf_group = lowering.copy_masters_to_slices()
      self.evaluate(tf_group)
      actual, expected = self.evaluate(
          [actual_outputs, expected_outputs]
      )
  
      self.assertAllEqual(actual, expected)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import mesh_tensorflow
  from mesh_tensorflow import test_utils
  import mock
  import numpy
  import tensorflow.compat.v1
  import tensorflow_probability
  from tensorflow.python.framework import test_util
label_desc: Use image node_id 6 for calling the LayersTest obj's underlying member method code with example usage: obj.testWeightsNonzero() without return types